Atanas Kiryakov: The purpose of maintaining an online process is to be able to classify and enrich content with more metadata. A typical media website contains 10 or 20 categories like specific regions in the world, which means there would typically be 10 to 30 web pages that are pretty much maintained by them. Their editors make decisions on
Sramana Mitra: Basically, you’re addressing regulatory issues for pharmaceutical companies. Then you’re helping some of these media companies reconcile and clarify their databases and perhaps even enhance their databases, which are then accessed by their clients. That’s the other use case that you talked about, right? Atanas Kiryakov: Yes. We also help pharmaceutical companies with
Atanas Kiryakov: If you want to solve this problem of massive data with any relational database, you’d probably need to hire several hundred people. Currently, we have just two employees working to maintain this data warehouse in our offices. Even at this scale, the ratio between the effort that we need to do and the effort
Sramana Mitra: Let me drill down a bit. I don’t know if you’re familiar with my writings on this subject. I’ve written extensively on this topic. What I’d like to do is take three of your customers from three different domains, and do some use cases on how you’re applying AI technology, that you built
Semantic technologies are gaining ground in the world of Big Data. This interview focuses on some applications in various parts of the industry. Sramana Mitra: Let’s start by introducing the audience to Ontotext. Tell us who you are, where you’re based, and what kind of work you are doing. Atanas Kiryakov: I founded Ontotext in the year